Processing Multidimensional Models

Understanding Processing

When you process a multidimensional cube or related objects (dimensions, measure groups, partitions), Analysis Services performs several tasks:

• Reads data from relational sources.
• Transforms and aggregates data according to dimension hierarchies and measure definitions.
• Stores the processed data in an optimized format for fast querying.
• Updates dimension attributes and measures.

Processing ensures that the data in your cube is up-to-date and accurate. There are different processing modes, each suited for different scenarios:

• Full Process: Clears existing data and metadata, then recreates and populates all objects. Use this when structural changes have been made or for a complete refresh.
• Process Default: Processes objects that have not been processed or require reprocessing. This is the most common choice for incremental updates.
• Process Data: Populates existing, processed objects with new data. Does not affect metadata.
• Process Add: Adds new data to existing partitions. Useful for incremental loading where new data is appended.
• Process Update: Updates existing data with new or changed values.
• Process Clear: Clears data from partitions but retains the metadata.
• Process Recalc: Recalculates aggregations for processed measure groups without reloading data.

Processing Methods

You can initiate processing operations through various tools and methods:

SQL Server Management Studio (SSMS)

1. Connect to your Analysis Services instance in SSMS.
2. Expand your database, then expand "Cubes" or "Dimensions".
3. Right-click the object you want to process (e.g., a cube, a dimension, a measure group).
4. Select "Process...".
5. In the "Process Designer" dialog, choose the processing mode and select the objects to process.
6. Click "OK".

SQL Server Data Tools (SSDT)

During deployment from SSDT to an Analysis Services instance, you can configure processing options:

1. In SSDT, right-click the project name in Solution Explorer.
2. Select "Properties".
3. Navigate to the "Deployment" tab.
4. Configure the "Processing Option" for the deployment.

You can also initiate processing directly from SSDT by right-clicking a cube or dimension in Solution Explorer and selecting "Process".

AMO (Analysis Management Objects) and XMLA

For automated processing and scripting, you can use AMO libraries in .NET or send XML for Analysis (XMLA) commands.

<!-- Example XMLA command for processing a cube -->
<Batch xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
  <Parallel xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
    <Process xmlns="http://schemas.microsoft.com/analysisservices/2003/engine">
      <Object>
        <DatabaseID>YourDatabaseName</DatabaseID>
        <CubeID>YourCubeName</CubeID>
      </Object>
      <Type>ProcessFull</Type>
      <State>DataMorphin</State>
    </Process>
  </Parallel>
</Batch>
            

Processing Specific Objects

You can choose to process the entire cube, or individual components:

• Dimensions: Processing a dimension populates its attribute data. If a dimension is shared across multiple cubes, processing it once updates it for all.
• Measure Groups: Processing a measure group loads and aggregates the fact data for the measures within it.
• Partitions: Partitions are the physical storage units for measure group data. Processing a partition loads data into that specific segment.
• Aggregations: Aggregations can be processed or recalculated to improve query performance.

Processing Performance and Best Practices

• Incremental Processing: Implement incremental processing for fact tables that are frequently updated to avoid full reprocessing. This involves identifying new or changed records and processing only those.
• Partitioning: Divide large tables into smaller, manageable partitions (e.g., by date). This allows for more granular processing and better performance.
• Pre-calculated Aggregations: Design and process aggregations to significantly speed up query responses.
• Scheduled Processing: Use SQL Server Agent jobs to schedule regular processing of your SSAS models during off-peak hours.
• Error Handling: Configure error handling for processing jobs to log issues and notify administrators.
• Monitoring: Monitor processing job durations and success rates to identify performance bottlenecks.

Troubleshooting Processing Errors

Common processing errors can arise from:

• Data source connection issues.
• Insufficient permissions for the SSAS service account.
• Data type mismatches or invalid data in the source.
• Violations of unique key constraints in dimensions.
• Network connectivity problems.

Review the SSAS logs and the error messages provided by SSMS or other tools for detailed information to diagnose and resolve issues.